回答

流式输出

from google import genai

client = genai.Client()

response = client.models.generate_content_stream(
    model="gemini-2.5-flash",
    contents=["Explain how AI works"]
)
for chunk in response:
    print(chunk.text, end="")

from PIL import Image
from google import genai

client = genai.Client()

image = Image.open("/path/to/organ.png")
response = client.models.generate_content(
    model="gemini-2.5-flash",
    contents=[image, "Tell me about this instrument"]
)
print(response.text)

增加系统提示词

from google import genai
from google.genai import types

client = genai.Client()

response = client.models.generate_content(
    model="gemini-2.5-flash",
    config=types.GenerateContentConfig(
        system_instruction="You are a cat. Your name is Neko."),
    contents="Hello there"
)

print(response.text)

默认flash模型是启用了推理模式，可以关闭的

from google import genai
from google.genai import types

client = genai.Client()

response = client.models.generate_content(
    model="gemini-2.5-flash",
    contents="How does AI work?",
    config=types.GenerateContentConfig(
        thinking_config=types.ThinkingConfig(thinking_budget=0) # Disables thinking
    ),
)
print(response.text)

from google import genai

client = genai.Client()
chat = client.chats.create(model="gemini-2.5-flash")

response = chat.send_message_stream("I have 2 dogs in my house.")
for chunk in response:
    print(chunk.text, end="")

response = chat.send_message_stream("How many paws are in my house?")
for chunk in response:
    print(chunk.text, end="")

for message in chat.get_history():
    print(f'role - {message.role}', end=": ")
    print(message.parts[0].text)